U.S. patent application number 11/165562 was filed with the patent office on 2006-09-28 for method and apparatus for voice quality enhancement.
This patent application is currently assigned to Tellabs Operations, Inc.. Invention is credited to Rafid A. Sukkar, Richard C. Younce, Peng Zhang.
Application Number | 20060215683 11/165562 |
Document ID | / |
Family ID | 37035099 |
Filed Date | 2006-09-28 |
United States Patent
Application |
20060215683 |
Kind Code |
A1 |
Sukkar; Rafid A. ; et
al. |
September 28, 2006 |
Method and apparatus for voice quality enhancement
Abstract
Voice Quality Enhancement (VQE) is performed directly in a coded
domain. A Coded Domain Voice Quality Enhancement (CD-VQE) system
modifies at least one parameter of a first encoded signal,
resulting in corresponding modified parameter(s). The CD-VQE system
replaces the parameter(s) of the first encoded signal with the
modified parameter(s), resulting in a second encoded signal. In a
decoded state, the second encoded signal approximates a target
signal that is a function of at least the first encoded signal in
at least a partially decoded state. Thus, the first encoded signal
does not have to go through intermediate decode/re-encode
processes, which can degrade overall speech quality. The CD-VQE
system may cascade functions. Computational resources required for
a complete re-encoding are not needed. Overall delay of the system
is minimized. The CD-VQE system can be used in networks in which
signals are communicated in a coded domain, such as a Third
Generation (3G) wireless network.
Inventors: |
Sukkar; Rafid A.; (Aurora,
IL) ; Younce; Richard C.; (Yorkville, IL) ;
Zhang; Peng; (Buffalo Grove, IL) |
Correspondence
Address: |
HAMILTON, BROOK, SMITH & REYNOLDS, P.C.
530 VIRGINIA ROAD
P.O. BOX 9133
CONCORD
MA
01742-9133
US
|
Assignee: |
Tellabs Operations, Inc.
Naperville
IL
|
Family ID: |
37035099 |
Appl. No.: |
11/165562 |
Filed: |
June 22, 2005 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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60665910 |
Mar 28, 2005 |
|
|
|
60665911 |
Mar 28, 2005 |
|
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Current U.S.
Class: |
370/437 ;
370/252; 370/328; 455/452.2; 704/E19.035; 704/E21.009 |
Current CPC
Class: |
G10L 19/12 20130101;
G10L 21/0364 20130101; H04B 3/20 20130101 |
Class at
Publication: |
370/437 ;
370/252; 370/328; 455/452.2 |
International
Class: |
H04J 1/16 20060101
H04J001/16; H04L 12/26 20060101 H04L012/26; H04J 3/16 20060101
H04J003/16; H04Q 7/20 20060101 H04Q007/20; H04Q 7/00 20060101
H04Q007/00 |
Claims
1. A method of modifying an encoded signal, comprising: modifying
at least one parameter of a first encoded signal resulting in a
corresponding at least one modified parameter; and replacing the at
least one parameter of the first encoded signal with the at least
one modified parameter resulting in a second encoded signal which,
in a decoded state, approximates a target signal that is a function
of at least the first encoded signal in at least a partially
decoded state.
2. The method according to claim 1 wherein modifying the at least
one parameter includes computing the target signal by cascading at
least two of the following functions: echo suppression, noise
reduction, adaptive level control, or adaptive gain control.
3. The method according to claim 1 further including computing a
target scale factor that is a function of the target signal and at
least the first encoded signal in at least a partially decoded
state.
4. The method according to claim 3 wherein computing the target
scale factor includes computing a square root of a ratio of
energies of corresponding segments of the target signal and at
least the first encoded signal in at least a partially decoded
state or computing a median or average of the ratio of the absolute
values of the samples of corresponding segments of the target
signal and at least the first encoded signal in at least a
partially decoded state.
5. The method according to claim 1 wherein modifying the at least
one parameter includes modifying a fixed codebook gain parameter
and an adaptive codebook gain parameter.
6. The method according to claim 1 wherein modifying the at least
one parameter includes modifying at least one of the following
parameters: fixed codebook gain parameter, adaptive codebook gain
parameter, fixed codebook vector, pitch lag parameter, or Linear
Predictive Coding (LPC) filter parameters.
7. The method according to claim 1 wherein the first and second
encoded signals are Code Excited Linear Prediction (CELP) encoded
signals.
8. The method according to claim 1 further including calculating an
adaptive codebook gain.
9. The method according to claim 8 wherein calculating an adaptive
codebook gain includes: (i) computing a target scale factor that is
a function of the target signal and at least the first encoded
signal in at least a partially decoded state; (ii) computing an
adaptive codebook scale factor that is equal to the target scale
factor multiplied by a square root of a ratio of (a) energy of an
adaptive codebook vector corresponding to the first encoded signal
to (b) energy of an adaptive codebook vector corresponding to the
second codebook signal; (iii) multiplying the adaptive codebook
scale factor by an adaptive codebook gain resulting in a modified,
adaptive codebook gain; and (iv) quantizing the modified, adaptive
codebook gain resulting in a quantized, modified, adaptive
codebook, gain parameter; and wherein replacing the at least one
parameter includes replacing an adaptive codebook gain parameter in
an encoded state with the quantized, modified, adaptive codebook,
gain parameter.
10. The method according to claim 1 further including calculating a
fixed codebook gain.
11. The method according to claim 10 wherein calculating a fixed
codebook gain includes: (i) computing a target scale factor that is
a function of the target signal and at least the first encoded
signal in at least a partially decoded state; (ii) calculating
roots of an equation obtained by equating (a) energy of excitation
of the first encoded signal multiplied by the target scale factor
squared to (b) energy of excitation of the second encoded signal;
(iii) (A) assigning a fixed codebook scale factor to the ration of
a value of a real, positive root of the equation, if it exists, to
the fixed codebook gain parameter in a decoded state, or (B)
assigning the fixed codebook scale factor to zero if it does not
exist and (1) calculating an adaptive codebook scale factor to be
the target scale factor multiplied by the square root of a ratio of
(a) energy of excitation of the first encoded signal to (b) energy
of the adaptive codebook vector of the second encoded signal, (2)
multiplying the adaptive codebook scale factor by an adaptive
codebook gain in a decoded state resulting in a modified, adaptive
codebook gain, and (3) quantizing the modified, adaptive codebook
gain resulting in a quantized, modified, adaptive codebook, gain
parameter; (iv) multiplying the fixed codebook scale factor by a
fixed codebook gain parameter in a decoded state resulting in a
modified, fixed codebook gain; (v) quantizing the modified, fixed
codebook gain resulting in a quantized, modified, fixed codebook,
gain parameter; and wherein replacing the at least one parameter
includes (a) replacing a fixed codebook gain parameter in an
encoded state with the quantized, modified, fixed codebook, gain
parameter, and, if a value of a real positive root of the equation
does not exist, (b) replacing an adaptive codebook gain parameter
in an encoded state with the quantized, modified, adaptive
codebook, gain parameter.
12. The method according to claim 1 wherein modifying the at least
one parameter performs at least one of the following processes:
suppressing echoes, reducing noise, adaptively controlling signal
levels, or adaptively controlling signal gain.
13. The method according to claim 1 used for voice quality
enhancement.
14. An apparatus for modifying an encoded signal, comprising at
least: a decoder at least partially decoding a first encoded signal
into a corresponding linear domain signal in at least a partially
decoded state and decoding at least one encoded parameter of the
first encoded signal resulting in a corresponding at least one
parameter in a decoded state; a linear domain processor generating
a target signal as a function of at least the first encoded signal
in the at least partially decoded state; a coded domain processor
(i) modifying the at least one parameter in a decoded state
resulting in a corresponding at least one modified parameter and
(ii) replacing the at least one encoded parameter of the first
encoded signal with the at least one modified parameter in an
encoded state resulting in a second encoded signal, which, when
decoded, approximates the target signal.
15. The apparatus according to claim 14 wherein the linear
processor generates the target signal by cascading at least two of
the following functions: echo suppression, noise reduction,
adaptive level control, or adaptive gain control; and wherein, in
the case of including echo suppression or adaptive gain control,
the apparatus further includes a second decoder at least partially
decoding a third encoded signal into a corresponding linear domain
signal in at least a partially decoded state.
16. The apparatus according to claim 14 wherein the coded domain
processor includes a scale computation unit that calculates a
target scale factor as a function of the target signal and at least
the first encoded signal in a partially decoded state.
17. The apparatus according to claim 16 wherein the scale
computation unit calculates the target scale factor by computing a
square root of a ratio of energies of corresponding segments of the
target signal and at least the first encoded signal in at least a
partially decoded state or computing a median or average of the
ratio of the absolute values of the samples of corresponding
segments of the target signal and at least the first encoded signal
in at least a partially decoded state.
18. The apparatus according to claim 14 wherein the at least one
modified parameter includes a fixed codebook gain parameter and an
adaptive codebook gain parameter.
19. The apparatus according to claim 14 wherein the at least one
modified parameter includes at least one of the following
parameters: fixed codebook gain parameter, adaptive codebook gain
parameter, fixed codebook vector, pitch lag parameter, or Linear
Predictive Coding (LPC) filter parameters.
20. The apparatus according to claim 14 wherein the encoded signal
is a Code Excited Linear Prediction (CELP) encoded signal.
21. The apparatus according to claim 14 wherein the decoder is a
first decoder and wherein the coded domain processor further
includes: a scale computation unit that calculates a target scale
factor as a function of the target signal and at least the first
encoded signal in a partially decoded state; a second decoder at
least partially decoding the second encoded signal and outputting
at least a partial adaptive codebook vector; and a coded domain
parameter modification unit that computes the at least one modified
parameter as a function of the target scale factor, at least one
decoded parameter, at least partial adaptive codebook vector, and
at least one modified parameter.
22. The apparatus according to claim 21 wherein, if the linear
processor generates the target signal by cascading echo suppression
or adaptive gain control, the apparatus further includes a third
decoder at least partially decoding a third encoded signal into a
corresponding linear domain signal in at least a partially decoded
state.
23. The apparatus according to claim 14 wherein the coded domain
processor calculates an adaptive codebook gain.
24. The apparatus according to claim 23 wherein, to calculate the
adaptive codebook gain, the coded domain processor: (i) computes a
target scale factor that is a function of the target signal and at
least the first encoded signal in at least a partially decoded
state; (ii) computes an adaptive codebook scale factor that is
equal to the target scale factor multiplied by a square root of a
ratio of (a) energy of an adaptive codebook vector corresponding to
the first encoded signal to (b) energy of an adaptive codebook
vector corresponding to the second codebook signal; (iii)
multiplies the adaptive codebook scale factor by an adaptive
codebook gain resulting in a modified, adaptive codebook gain; (iv)
quantizes the modified adaptive codebook gain resulting in a
quantized, modified, adaptive codebook, gain parameter; and (v)
replaces an adaptive codebook, gain parameter in an encoded state
with the quantized, modified, adaptive codebook, gain
parameter.
25. The apparatus according to claim 14 wherein the coded domain
processor calculates a fixed codebook gain.
26. The apparatus according to claim 25 wherein to calculate the
fixed codebook gain, the coded domain processor: (i) computes a
target scale factor that is a function of the target signal and at
least the first encoded signal in at least a partially decoded
state; (ii) calculates roots of an equation obtained by equating
(a) energy of excitation of the first encoded signal multiplied by
the target scale factor squared to (b) energy of excitation of the
second encoded signal; (iii) assigns a fixed codebook scale factor
to the ratio of a value of a real, positive root of the equation,
if it exists, to the fixed codebook gain parameter in a decoded
state, or assigns the fixed codebook scale factor to zero if it
does not exist and (a) calculates an adaptive codebook scale factor
to be the target scale factor multiplied by the square root of a
ratio of (1) energy of excitation of the first encoded signal to
(2) energy of the adaptive codebook vector of the second encoded
signal, (b) multiplies the adaptive codebook scale factor by an
adaptive codebook gain resulting in a modified, adaptive codebook
gain, and (c) quantizes the modified, adaptive codebook, gain
resulting in a quantized, modified, adaptive codebook, gain
parameter; (iv) multiplies the fixed codebook scale factor by a
fixed codebook gain parameter in a decoded state resulting in a
modified, fixed, codebook gain; (v) quantizes the modified, fixed
codebook gain resulting in a quantized, modified, fixed codebook,
gain parameter; and (vi) (a) replaces a fixed codebook gain
parameter in an encoded state with the quantized, modified, fixed
codebook, gain parameter, and, if a value of a real positive root
of the equation does not exist, (b) replaces an adaptive codebook
gain parameter in an encoded state with the quantized, modified,
adaptive codebook, gain parameter.
27. The apparatus according to claim 14 operating as at least one
of the following: echo suppressor, noise reducer, adaptive level
controller, or adaptive signal gain controller.
28. The apparatus according to claim 14 used in a voice quality
enhancer.
29. The apparatus according to claim 14 implemented in at least one
of the following forms: software executed by a processor, firmware,
or hardware.
Description
RELATED APPLICATION(S)
[0001] This application claims the benefit of U.S. Provisional
Application No. 60/665,910 filed Mar. 28, 2005, entitled, "Method
and Apparatus for Performing Echo Suppression in a Coded Domain,"
and U.S. Provisional Application No. 60/665,911 filed Mar. 28,
2005, entitled, "Method and Apparatus for Performing Echo
Suppression in a Coded Domain." The entire teachings of these
provisional applications are incorporated herein by reference.
BACKGROUND OF THE INVENTION
[0002] Speech compression represents a basic operation of many
telecommunications networks, including wireless and
voice-over-Internet Protocol (VoIP) networks. This compression is
typically based on a source model, such as Code Excited Linear
Prediction (CELP). Speech is compressed at a transmitter based on
the source model and then encoded to minimize valuable channel
bandwidth that is required for transmission. In many newer
generation networks, such as Third Generation (3G) wireless
networks, the speech remains in a Coded Domain (CD) (i.e.,
compressed) even in a core network and is decompressed and
converted back to a Linear Domain (LD) at a receiver. This
compressed data transmission through a core network is in contrast
with cases where the core network has to decompress the speech in
order to perform its switching and transmission. This intermediate
decompression introduces speech quality degradation. Therefore, new
generation networks try to avoid decompression in the core network
if both sides of the call are capable of compressing/decompressing
the speech.
[0003] In many networks, especially wireless networks, a network
operator (i.e., service provider) is motivated to offer a
differentiating service that not only attracts customers, but also
keeps existing ones. A major differentiating feature is voice
quality. So, network operators are motivated to deploy in their
network Voice Quality Enhancement (VQE). VQE includes: acoustic
echo suppression, noise reduction, adaptive level control, and
adaptive gain control.
[0004] Echo cancellation, for example, represents an important
network VQE function. While wireless networks do not suffer from
electronic (or hybrid) echoes, they do suffer from acoustic echoes
due to an acoustic coupling between the ear-piece and microphone on
an end user terminal. Therefore, acoustic echo suppression is
useful in the network.
[0005] A second VQE function is a capability within the network to
reduce any background noise that can be detected on a call.
Network-based noise reduction is a useful and desirable feature for
service providers to provide to customers because customers have
grown accustomed to background noise reduction service.
[0006] A third VQE function is a capability within the network to
adjust a level of the speech signal to a predetermined level that
the network operator deems to be optimal for its subscribers.
Therefore, network-based adaptive level control is a useful and
desirable feature.
[0007] A fourth VQE function is adaptive gain control, which
reduces listening effort on the part of a user and improves
intelligibility by adjusting a level of the signal received by the
user according to his or her background noise level. If the
subscriber background noise is high, adaptive level control tries
to increase the gain of the signal that is received by the
subscriber.
[0008] In the older generation networks, where the core network
decompresses a signal into the linear domain followed by conversion
into a Pulse Code Modulation (PCM) format, such as A-law or
.mu.-law, in order to perform switching and transmission,
network-based VQE has access to the decompressed signals and can
readily operate in the linear domain. (Note that A-law and .mu.-law
are also forms of compression (i.e., encoding), but they fall into
a category of waveform encoders. Relevant to VQE in a coded domain
is source-model encoding, which is a basis of most low bit rate,
speech coding.) However, when voice quality enhancement is
performed in the network where the signals are compressed, there
are basically two choices: a) decompress (i.e., decode) the signal,
perform voice quality enhancement in the linear domain, and
re-compress (i.e., re-encode) an output of the voice quality
enhancement, or b) operate directly on the bit stream representing
the compressed signal and modify it directly to effectively perform
voice quality enhancement. The advantages of choice (b) over choice
(a) are three fold:
[0009] First, the signal does not have to go through an
intermediate decode/re-encode, which can degrade overall speech
quality. Second, since computational resources required for
encoding are relatively high, avoiding another encoding step
significantly reduces the computational resources needed. Third,
since encoding adds significant delays, the overall delay of the
system can be minimized by avoiding an additional encoding
step.
[0010] Performing VQE functions or combinations thereof in the
compressed (or coded) domain, however, represents a more
challenging task than VQE in the decompressed (or linear)
domain.
SUMMARY OF THE INVENTION
[0011] A method or corresponding apparatus in an exemplary
embodiment of the present invention performs Coded Domain Voice
Quality Enhancement (CD-VQE) by first modifying at least one
parameter of the first encoded signal, which results in a
corresponding at least one modified parameter. The method and
corresponding apparatus then replaces the at least one parameter of
the first encoded signal with the at least one modified parameter,
which results in a second encoded signal. In a decoded state, the
second encoded signal approximates a target signal that is a
function of at least the first encoded signal in at least a
partially decoded state. The CD-VQE may include cascading at least
two of the following functions: echo suppression, noise reduction,
adaptive level control, or adaptive gain control.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] The foregoing and other objects, features and advantages of
the invention will be apparent from the following more particular
description of preferred embodiments of the invention, as
illustrated in the accompanying drawings in which like reference
characters refer to the same parts throughout the different views.
The drawings are not necessarily to scale, emphasis instead being
placed upon illustrating the principles of the invention.
[0013] FIG. 1 is a network diagram of a network in which a system
performing Coded Domain Voice Quality Enhancement (CD-VQE) using an
exemplary embodiment of the present invention is deployed;
[0014] FIG. 2 is a high level view of the CD-VQE system of FIG.
1;
[0015] FIG. 3A is a detailed block diagram of the CD-VQE system of
FIG. 1;
[0016] FIG. 3B is a flow diagram corresponding to the CD-VQE system
of FIG. 3A;
[0017] FIG. 4 is a network diagram in which the CD-VQE processor of
FIG. 1 is performing Coded Domain Acoustic Echo Suppression
(CD-AES);
[0018] FIG. 5 is a block diagram of a CELP synthesizer used in the
coded domain embodiments of FIGS. 1 and 4 and other coded domain
embodiments;
[0019] FIG. 6 is a high level block diagram of the CD-AES system of
FIG. 4;
[0020] FIG. 7A is a detailed block diagram of the CD-AES system of
FIG. 4;
[0021] FIG. 7B is a flow diagram corresponding to the CD-AES system
of FIG. 7A;
[0022] FIG. 8 is a plot of a decoded speech signal processed by the
CD-AES system of FIG. 4;
[0023] FIG. 9 is a plot of an energy contour of the speech signal
of FIG. 8;
[0024] FIG. 10 is a plot of a synthesis LPC excitation energy scale
ratio corresponding to the energy contour of FIG. 9;
[0025] FIG. 11 is a plot of a decoded speech energy contour
resulting from Joint Codebook Scaling (JCS) used in the CD-AES
system of FIG. 7A;
[0026] FIG. 12 is a plot of a decoded speech energy contour for
fixed codebook scaling shown for comparison purposes to FIG.
11;
[0027] FIG. 13A is a detailed block diagram corresponding to the
CD-AES system of FIG. 7A further including Spectrally Matched Noise
Injection (SMNI);
[0028] FIG. 13B is a flow diagram corresponding to the CD-AES
system of FIG. 13A;
[0029] FIG. 14 is a network diagram including a Coded Domain Noise
Reduction (CD-NR) system optionally included in the CD-VQE system
of FIG. 1;
[0030] FIG. 15 is a high level block diagram of the CD-NR system of
FIG. 14;
[0031] FIG. 16A is a detailed block diagram of the CD-NR system of
FIG. 15 using a first method;
[0032] FIG. 16B is a flow diagram corresponding to the CD-NR system
of FIG. 16A;
[0033] FIG. 17A is a detailed block diagram of the CD-NR system of
FIG. 15 using a second method.
[0034] FIG. 17B is a flow diagram corresponding to the CD-NR system
of FIG. 17A;
[0035] FIG. 18 is a block diagram of a network employing a Coded
Domain Adaptive Level Control (CD-ALC) optionally provided in the
CD-VQE system of FIG. 1;
[0036] FIG. 19 is a high level block diagram of the CD-ALC system
of FIG. 18;
[0037] FIG. 20A is a detailed block diagram of the CD-ALC system of
FIG. 19;
[0038] FIG. 20B is a flow diagram corresponding to the CD-ALC
system of FIG. 20A;
[0039] FIG. 21 is a network diagram using a Coded Domain Adaptive
Gain Control (CD-AGC) system optionally used in the CD-VQE system
of FIG. 1;
[0040] FIG. 22 is a high level block diagram of the CD-AGC system
of FIG. 21;
[0041] FIG. 23A is detailed block diagram of the CD-AGC system of
FIG. 22;
[0042] FIG. 23B is a flow diagram corresponding to the CD-AGC
system of FIG. 23A; and
[0043] FIG. 24 is a network diagram of a network including Second
Generation (2G), Third Generation (3G) networks, VoIP networks, and
the CD-VQE system of FIG. 1, or subsets thereof, distributed about
the network.
DETAILED DESCRIPTION OF THE INVENTION
[0044] A description of preferred embodiments of the invention
follows.
[0045] Coded Domain Voice Quality Enhancement
[0046] A method and corresponding apparatus for performing Voice
Quality Enhancement (VQE) directly in the coded domain using an
exemplary embodiment of the present invention is presented below.
As should become clear, no intermediate decoding/re-encoding is
performed, thereby avoiding speech degradation due to tandem
encodings and also avoiding significant additional delays.
[0047] FIG. 1 is a block diagram of a network 100 including a Coded
Domain VQE (CD-VQE) system 130a. For simplicity, the CD-VQE system
130a is shown on only one side of a call with an understanding that
CD-VQE can be performed on both sides. The one side of the call is
referred to herein as the near end 135a, and the other side of the
call is referred to herein as the far end 135b.
[0048] In FIG. 1, the CD-VQE system 130a is performed on a send-in
signal (si) 140a generated by a near end user 105a using a near end
wireless telephone 110a. A far end user 105b using a far end
telephone 110b communicates with the near end user 105a via the
network 100. A near end Adaptive Multi-Rate (AMR) coder 115a and a
far end AMR coder 115b are employed to perform encoding/decoding in
the telephones 115a, 115b. A near end base station 125a and a far
end base station 125b support wireless communications for the
telephones 110a, 110b, including passing through compressed speech
120. Another example includes a network 100 in which the near end
wireless telephone 110a may also be in communication with a base
station 125a, which is connected to a media gateway (not shown),
which in turn communicates with a conventional wireline telephone
or Public Switched Telephone Network (PSTN).
[0049] In FIG. 1, a receive-in signal, ri, 145a, send-in signal,
si, 140a, and send-out signal, so, 140b are bit streams
representing the compressed speech 120. Focus herein is on the
CD-VQE system 130a operating on the send-in signal, si, 140a.
[0050] The CD-VQE method and corresponding apparatus disclosed
herein is, by way of example, directed to a family of speech coders
based on Code Excited Linear Prediction (CELP). According to an
exemplary embodiment of the present invention, an Adaptive
Multi-Rate (AMR) set of coders is considered an example of CELP
coders. However, the method for the CD-VQE disclosed herein is
directly applicable to all coders based on CELP. Coders based on
CELP can be found in both mobile phones (i.e., wireless phones) as
well as wireline phones operating, for example, in a
Voice-over-Internet Protocol (VOIP) network. Therefore, the method
for CD-VQE disclosed herein is directly applicable to both wireless
and wireline communications.
[0051] Typically, a CELP-based speech encoder, such as the AMR
family of coders, segments a speech signal into frames of 20 msec.
in duration. Further segmentation into subframes of 5 msec. may be
performed, and then a set of parameters may be computed, quantized,
and transmitted to a receiver (i.e., decoder). If m denotes a
subframe index, a synthesizer (decoder) transfer function is given
by D m .function. ( z ) = S .function. ( z ) C m .function. ( z ) =
g c .function. ( m ) [ 1 - g p .function. ( m ) .times. z - T
.function. ( m ) ] .function. [ 1 - i = 1 p .times. a i .function.
( m ) .times. z - i ] ( 1 ) ##EQU1##
[0052] where S(z) is a z-transform of the decoded speech, and the
following parameters are the coded-parameters that are computed,
quantized, and sent by the encoder:
[0053] g.sub.c(m) is the fixed codebook gain for subframe m,
[0054] g.sub.p(m) is the adaptive codebook gain for subframe m,
[0055] T(m) is the pitch value for subframe m,
[0056] {a.sub.i(m)} is the set of P linear predictive coding
parameters for subframe m, and
[0057] C.sub.m(z) is the z-transform of the fixed codebook vector,
c.sub.m(n), for subframe m.
[0058] FIG. 5 is a block diagram of a synthesizer used to perform
the above synthesis. The synthesizer includes a long term
prediction buffer 505, used for an adaptive codebook, and a fixed
codebook 510, where
[0059] v.sub.m(n) is the adaptive codebook vector for subframe
m,
[0060] w.sub.m(n) is the Linear Predictive Coding (LPC) excitation
signal for subframe m, and
[0061] H.sub.m(z) is the LPC filter for subframe m, given by H m
.function. ( z ) = 1 1 - i = 1 p .times. a i .function. ( m )
.times. z - i ( 2 ) ##EQU2##
[0062] Based on the above equation, one can write
s(n)=w.sub.m(n)*h.sub.m(n) (3)
[0063] where h.sub.m(m) is the impulse response of the LPC filter,
and w.sub.m(n)=g.sub.p(m)v.sub.m(n)+g.sub.c(m)c.sub.m(n) (4)
[0064] FIG. 2 is a block diagram of an exemplary embodiment of a
CD-VQE system 200 that can be used to implement the CD-VQE system
130a introduced in FIG. 1. A Coded Domain VQE method and
corresponding apparatus are described herein whose performance
matches the performance of a corresponding Linear-Domain VQE
technique. To accomplish this matching performance, after
performing Linear-Domain VQE (LD-VQE), the CD-VQE system 200
extracts relevant information from the LD-VQE. This information is
then passed to a Coded Domain VQE.
[0065] Specifically, FIG. 2 is a high level block diagram of the
approach taken. In this figure, only the near-end side 135a of the
call is shown, where VQE is performed on the send-in bit stream,
si, 140a. The send-in and receive-in bit streams 140a, 145a are
decoded by AMR decoders 205a, 205b (collectively 205) into the
linear domain, si(n) and ri(n) signals 210a, 210b, respectively,
and then passed through a linear domain VQE system 220 to enhance
the si(n) signal 210a. The LD-VQE system 220 can include one or
more of the functions listed above (i.e., acoustic echo
suppression, noise reduction, adaptive level control, or adaptive
gain control). Relevant information is extracted from both the
LD-VQE 220 and the AMR decoder 205, and then passed to a coded
domain processing unit 230a. The coded domain processing unit 230a
modifies the appropriate parameters in the si bit stream 140a to
effectively perform VQE.
[0066] It should be understood that the AMR decoding 205 can be a
partial decoding of the two signals 140a, 145a. For example, since
most LD-VQE systems 220 are typically concerned with determining
signal levels or noise levels, a post-filter (not shown) present in
the AMR decoders 205 need not be implemented. It should further be
understood that, although the si signal 140a is decoded into the
linear domain, there is no intermediate decoding/re-encoding that
can degrade the speech quality. Rather, the decoded signal 210a is
used to extract relevant information 215, 225 that aids the coded
domain processor 230a and is not re-encoded after the LD-VQE
processor 220.
[0067] FIG. 3A is a block diagram of an exemplary embodiment of a
CD-VQE system 300 that can be used to implement the CD-VQE systems
130a, 200. In this embodiment, an exemplary embodiment of a LD-VQE
system 304, used to implement the LD-VQE system 220 of FIG. 2,
includes four processors 305a, 305b, 305c, and 305d of LD-VQE, But,
in general, any number of LD-VQE processors 305a-d can be cascaded
in exemplary embodiments of the present invention. In exemplary
embodiments of the present invention, the problem(s) of VQE in the
coded domain are transformed from the processor(s) themselves to
one of scaling the signal 140a on a segment-by-segment basis.
[0068] An exemplary embodiment of a coded domain processor 302 can
be used to implement the coded domain processor 230a introduced in
reference to FIG. 2. In the coded domain processor 302 of FIG. 3, a
scaling factor G(m) 315 for a given segment is determined by a
scale computation unit 310 that computes power or level ratios
between the output signal of the LD-VQE 304 and the linear domain
signal si(n) 210a. A "Coded Domain Parameter Modification" unit 320
in FIG. 3A employs a Joint Codebook Scaling (JCS) method. In JCS,
both a CELP adaptive codebook gain, g.sub.p(m), and a fixed
codebook gain, g.sub.c(m), are scaled, and the JCS outputs are the
scaled gains, g'.sub.p(m) and g'.sub.c(m). They are then quantized
by a quantizer 325 and inserted by a bit stream modification unit
335, also referred to herein as a replacing unit 335, in the
send-out bit stream, so, 140b, replacing the original gain
parameters present in the si bit stream 140a. These scaled gain
parameters, when used along with the other coder parameters 215 in
the AMR decoder 205a, produce a signal 140b that is an enhanced
version of the original signal, si(n), 210a.
[0069] A dequantizer 330 feeds back dequantized forms of the
quantized, adaptive codebook, scaled gain to the Coded Domain
Parameter Modification unit 320. Note that decoding the signal ri
145a into ri(n) 210b is used if one or more of the VQE processors
305a-d accesses ri(n) 210b. These processors include acoustic echo
suppression 305a and adaptive gain control 305d. If VQE does not
require access to ri(n) 210b, then decoding of ri 145a can be
removed from FIGS. 2 and 3A.
[0070] The operations in the CD-VQE system 300 shown in FIG. 3A are
summarized, and presented in the form of a flow diagram in FIG. 3B,
immediately below:
[0071] (i) The receive input signal bit stream ri 145a is decoded
into the linear domain signal, ri(n), 210b if required by the
LD-VQE processors 305a-d, specifically acoustic echo suppression
305a and adaptive gain control 305d.
[0072] (ii) The send-in bit stream signal si 140a is decoded into
the linear domain signal, si(n) 210a.
[0073] (iii) When more than one of the Linear Domain VQE processors
305a-d are used, the Linear-Domain VQE processors 305a-d may be
interconnected serially, where an input to one processor is the
output of the previous processor. The linear domain signal si(n)
210a is an input to the first processor (e.g., acoustic echo
suppression 305a), and the linear domain signal ri(n) 210b is a
potential input to any of the processors 305a-d. The LD-VQE output
signal 225 and the linear domain send-in signal si(n) 210a are used
to compute a scaling factor G(m) 315 on a frame-by-frame basis,
where m is the frame index. A frame duration of a scale computation
is equal to a subframe duration of the CELP coder. For example, in
an AMR 12.2 kbps coder, the subframe duration is 5 msec. The scale
computation frame duration is therefore set to 5 msec.
[0074] (iv) The scaling factor, G(m), is used to determine a
scaling factor for both the adaptive codebook gain g.sub.p(m) and
the fixed codebook gain and g.sub.c(m) parameters of the coder. The
Coded-Domain Parameter Modification unit 320 employs Joint Codebook
Scaling to scale g.sub.p(m) and g.sub.c(m).
[0075] (v) The scaled gains g'.sub.p(m) and g'.sub.c(m) are
quantized 325 and inserted 335 into the send-out bit stream, so,
140b by substituting the original quantized gains in the si bit
stream 140a.
[0076] Coded Domain Echo Suppression
[0077] A framework and corresponding method and apparatus for
performing acoustic echo suppression directly in the coded domain
using an exemplary embodiment of the present invention is now
described. As described above in reference to VQE, for acoustic
echo suppression performed directly in the coded domain, no
intermediate decoding/re-encoding is performed, which avoids speech
degradation due to tandem encodings and also avoids significant
additional delays.
[0078] FIG. 4 is a block diagram of a network 100 using a Coded
Domain Acoustic Echo Suppression (CD-AES) system 130b. In FIG. 4,
the receive-in signal, ri, 145a, the send-in signal, si, 140a, and
the send-out signal, so, 140b are bit streams representing
compressed speech 120.
[0079] The CD-AES method and corresponding apparatus 130b is
applicable to a family of speech coders based on Code Excited
Linear Prediction (CELP). According to an exemplary embodiment of
the present invention, the AMR set of coders 115 are considered an
example of CELP coders. However, the method for CD-AES presented
herein is directly applicable to all coders based on CELP
[0080] The Coded Domain Echo suppression method and corresponding
apparatus 130b meets or exceeds the performance of a corresponding
Linear Domain-Echo Suppression technique. To accomplish such
performance, a Linear-Domain Echo Acoustic Suppression (LD-AES)
unit 305a is used to provide relevant information, such as decoder
parameters 215 and linear-domain parameters 225. This information
215, 225 is then passed to a coded domain processing unit 230b.
[0081] FIG. 6 is a high level block diagram of an approach used for
performing Coded Domain Acoustic Echo Suppression (CD-AES), or
Coded Domain Echo Suppression (CD-ES) when the source of the echo
is other than acoustic. An exemplary CD-AES system 600 can be used
to implement the CD-AES system 130b of FIG. 4. In FIG. 6, both the
ri and si bit streams 145a, 140a are decoded into the linear domain
signals, ri(n) 210b and si(n) 210a, respectively. They are then
passed through a conventional LD-AES processor 305a to suppress
possible echoes in the si(n) signal 210a. Relevant information is
extracted from both LD-AES and the AMR decoding processes 305a and
205a, respectively, and then passed to the coded domain processor
230b. The coded domain processor 230b modifies appropriate
parameters in the si bit stream 140a to effectively suppress
possible echoes in the signal 140a.
[0082] It should be understood that the AMR decoding 205 can be a
partial decoding of the two signals 140a, 145a. For example, since
the LD-AES processor 305a is typically based on signal levels, the
post-filter present in the AMR decoders 205 need not be implemented
since it does not affect the overall level of the decoded signal.
It should further be understood that, although the si signal 140a
is decoded into the linear domain, there is no intermediate
decoding/re-encoding that can degrade the speech quality. Rather,
the decoded signal 210a is used to extract relevant information
that aids the coded domain processor 230b and is not re-encoded
after the LD-AES processor 305a.
[0083] FIG. 7A is a detailed block diagram of an exemplary
embodiment of a CD-AES system 700 that can be used to implement the
CD-AES systems 130b, 600 of FIGS. 4 and 6. Given the fact that the
outcome of a conventional LD-AES system 305a is to adaptively scale
the linear domain signal si(n) 210a so as to suppress any possible
echoes and pass through any near end speech, the coded domain echo
suppression unit 700 operates as follows: it modifies the bit
stream, si, 140a so that the resulting bit stream, so, 140b when
decoded, results in a signal, so(n), 210a that is as close as
possible to the linear domain echo-suppressed signal, si.sub.e(n),
also referenced to herein as a target signal. Therefore, since
si.sub.e(n) is typically a scaled version of si(n) 210a, the
problem of the coded domain echo suppression is transformed to a
problem of how properly to modify a given encoded signal bit stream
to result, when decoded, in an adaptively scaled version of the
signal corresponding to the original bit stream. The scaling factor
G(m) 315 is determined by the scale computation unit 310 by
comparing the energy of the signal si(n) 210a to the energy of the
echo suppressed signal si.sub.e(n).
[0084] Before addressing the coded domain scaling problem, a
summary of the operations in the CD-AES system 700 shown in FIG. 7A
is presented in the form of a flow diagram in FIG. 7B:
[0085] (i) The bit streams ri 145a and si 140a are decoded 205a,
205b into linear signals, ri(n) 210b and si(n) 210a.
[0086] (ii) A Linear-Domain Acoustic Echo Suppression processor
305a that operates on ri(n) 210b and si(n) 210a is performed. The
LD-AES processor 305a output is the signal si.sub.e(n), which
represents the linear domain send-in signal, si(n), 210a after
echoes have been suppressed.
[0087] (iii) A scale computation unit 310 determines the scaling
factor G(m) 315 between si(n) 210a and si.sub.e(n). A single
scaling factor, G(m), 315 is computed for every frame (or subframe)
by buffering a frame worth of samples of si(n) 210a and si.sub.e(n)
and determining a ratio between them. One possible method for
computing G(m) 315 is a simple power ratio between the two signals
in a given frame. Other methods include computing a ratio of the
absolute value of every sample of the two signals in a frame, and
then taking a median, or average of the sample ratio for the frame,
and assigning the result to G(m) 315. The scaling factor 315 can be
viewed as the factor by which a given frame of si(n) 210a has to be
scaled by to suppress possible echoes in the coded domain signal
140a. The frame duration of the scale computation is equal to the
subframe duration of the CELP coder. For example, in the AMR 12.2
bps coder, the subframe duration is 5 msec. The scale computation
frame duration is therefore set to 5 msec. also.
[0088] (iv) The scaling factor, G(m), 315 is used to determine 320
a scaling factor for both the adaptive codebook gain g.sub.p(m) and
the fixed codebook gain parameters g.sub.c(m) of the coder. The
Coded-Domain Parameter Modification unit 320 employs the Joint
Codebook Scaling method to scale g.sub.p(m) and g.sub.c(m).
[0089] (v) The scaled gains g.sub.p(m) and g.sub.c(m) are quantized
325 and inserted 335 into the send-out bit stream, so, 140b by
substituting the original quantized gains in the si bit stream
140a.
[0090] Signal Scaling in the Coded Domain
[0091] The problem of scaling the speech signal 140a by modifying
its coded parameters directly has applications not only in Acoustic
Echo Suppression, as described immediately above, but also in
applications such as Noise Reduction, Adaptive Level Control, and
Adaptive Gain Control, as are described below. Equation (1) above
suggests that, by scaling the fixed codebook gain, g.sub.c(m), by a
given factor, G, a corresponding speech signal, which is also
scaled by G, can be determined directly. However, this is true if
the synthesis transfer function, D.sub.m(z), is time-invariant.
But, it is clear that D.sub.m(z) is a function of the subframe
index, m, and, therefore, is not time-invariant.
[0092] Previous coded domain scaling methods that have been
proposed modify the fixed codebook gain, g.sub.c(m). See C.
Beaugeant, N. Duetsch, and H. Taddei, "Gain Loss Control Based on
Speech Codec Parameters," in Proc. European Signal Processing
Conference, pp. 409-412, September 2004. Other methods, such as
proposed by R. Chandran and D. J. Marchok, "Compressed Domain Noise
Reduction and Echo Suppression for Network Speech Enhancement," in
Proc. 43.sup.rd IEEE Midwest Symp. on Circuits and Systems, pp.
10-13, August 2000, try to adjust both gains based on some
knowledge of the nature of the given speech segment or subframe
(e.g., voiced vs. unvoiced).
[0093] In contrast, exemplary embodiments of the present invention
do not require knowledge of the nature of the speech subframe. It
is assumed that the scaling factor, G(m), 315 is calculated and
used to scale the linear domain speech subframe. This scaling
factor 315 can come from, for example, a linear-domain processor,
such as acoustic echo suppression processor, as discussed above.
Therefore, given G(m) 315, an analytical solution jointly scales
both the adaptive codebook gain, g.sub.p(m), and the fixed codebook
gain, g.sub.c(m), such that the resulting coded parameters, when
decoded, result in a properly scaled linear domain signal. This
joint scaling, described in detail below, is based on preserving a
scaled energy of an adaptive portion of the excitation signal, as
well as a scaled energy of the speech signal. This method is
referred to herein as Joint Codebook Scaling (JCS).
[0094] The Coded Domain Parameter Modification unit 320 in FIG. 7A
executes JCS. It has the inputs listed below. For simplicity and
without loss of generality, the subframe index, m, is dropped with
the understanding that the processing units can operate on a
subframe-by-subframe basis.
[0095] (i) The gain, G, is to be applied for a given subframe as
determined by the scale computation unit 310 following the LD-AES
processor 305a.
[0096] (ii) The adaptive and fixed codebook vectors, v(n) and c(n),
respectively, correspond to the original unmodified bit stream, si,
140a. These vectors are already determined in the decoder 205a that
produces si(n), 210a, as FIG. 7A shows. Therefore, they are readily
available to the JCS processor 320.
[0097] (iii) The adaptive and fixed codebook gains, g.sub.p and
g.sub.c, respectively, correspond to the original unmodified bit
stream, si, 140a. These gain parameters are already determined in
the decoder 205a that produces si(n) 210a. Therefore, they are
readily available to the scaling processor 310.
[0098] (iv) The adaptive codebook vector, v'(n), of the subframe
excitation signal corresponding to the modified (scaled) bit
stream, so, 140b is provided by the partial AMR decoder 340a.
[0099] (v) The scaled version of the adaptive codebook gain,
'.sub.p, after going through quantization/de-quantization
processors 325, 330, is fed back to the JCS processor 320.
[0100] Note that the decoder 340a operating on the send-out
modified bit stream, so, 140b need not be a full decoder. Since its
output is the adaptive codebook vector, the LPC synthesis operation
(H.sub.m(z) in FIG. 5) need not be performed in this decoder
340a.
[0101] Let x(n) be the near-end signal before it is encoded and
transmitted as the si bit stream 140a in FIG. 7A. Let g.sub.p be
the adaptive codebook gain for a given subframe corresponding to
x(n). According to the encoding, g.sub.p is computed as described
by Adaptive Multi-Rate (AMR): Adaptive Multi-Rate (AMR) Speech
Codec Transcoding Functions, 3.sup.rd Generation Partnership
Project Document number 3GPP TS 26.090, according to the following
equation: g p = n = 0 N - 1 .times. x .function. ( n ) .times. y
.function. ( n ) n = 0 N - 1 .times. y 2 .function. ( n ) ( 5 )
##EQU3##
[0102] where N is the number of samples in the subframe, and y(n)
is the filtered adaptive codebook vector given by: y(n)=v(n)*h(n)
(6)
[0103] Here, v(n) is the adaptive codebook vector, and h(n) is the
impulse response of the LPC synthesis filter.
[0104] If the near end speech input were scaled by G at any given
subframe, then the adaptive codebook gain is determined according
to g p ( s ) = n = 0 N - 1 .times. x .function. ( n ) .times. y
.function. ( n ) n = 0 N - 1 .times. y 2 .function. ( n ) = Gg p (
7 ) ##EQU4##
[0105] The resulting energy in the adaptive portion of the
excitation signal is therefore given by [ g p ( s ) ] 2 .times. n =
0 .times. N - 1 .times. v 2 .function. ( n ) = G 2 .times. g p 2
.times. n = 0 N - 1 .times. v 2 .function. ( n ) ( 8 ) ##EQU5##
[0106] The criterion used in scaling the adaptive codebook gain,
g.sub.p, is that the energy of the adaptive portion of the
excitation is preserved. That is, ( g p ' ) 2 .times. n = 0 .times.
N - 1 .times. ( v ' .function. ( n ) ) 2 = G 2 .times. g p 2
.times. n = 0 N - 1 .times. v 2 .function. ( n ) ( 9 ) ##EQU6##
[0107] where v'(n) is the adaptive codebook vector of the (partial)
decoder 340a operating on the scaled bit stream (i.e., the send-out
bit stream, so), and g'.sub.p is the scaled adaptive codebook gain
that is quantized 325 and inserted 335 into the bit stream 140a to
produce the send-out bit stream, so, 140b. Since the pitch lag is
preserved and not modified as part of the scaling, v'(n) is based
on the same pitch lag as v(n). However, since the scaled decoder
has a scaled version of the excitation history, v'(n) is different
from v(n).
[0108] The scaled adaptive codebook gain can be written as
g'.sub.p=K.sub.pg.sub.p (10)
[0109] where K.sub.p is the scaling factor for the adaptive
codebook gain. According to Equation (9), K.sub.p is given by: K p
= G .function. [ n = 0 N - 1 .times. v 2 .function. ( n ) n = 0 N -
1 .times. ( v ' .function. ( n ) ) 2 ] 1 / 2 ( 11 ) ##EQU7##
[0110] Turning now to the fixed codebook gain, the criterion used
in scaling g.sub.c is to preserve the speech signal energy. The
total subframe excitation at the decoder that operates on the
original bit stream, si, 140a is given by:
w(n)=g.sub.pv(n)+g.sub.cc(n) (12)
[0111] The energy of the resulting decoded speech signal in a given
subframe is E x = n = 0 N - 1 .times. ( w .function. ( n ) * h
.function. ( n ) ) 2 ( 13 ) ##EQU8##
[0112] where the initial conditions of the LPC filter, h(n), are
preserved from the previous subframe synthesis. If the speech is
scaled at any given subframe by G, then the speech energy becomes:
E x ( s ) = G 2 .times. n = 0 N - 1 .times. ( w .function. ( n ) *
h .function. ( n ) ) 2 = n = 0 N - 1 .times. ( Gw .function. ( n )
* h .function. ( n ) ) 2 ( 14 ) ##EQU9##
[0113] Therefore, scaling the speech is equivalent to scaling the
total excitation by G. This is generally true if the initial
conditions of h(n) are zero. However, an approximation is made that
this relationship still holds even when the initial conditions are
the true initial conditions of h(n). This approximation has an
effect that the scaling of the decoded speech does not happen
instantly. However, this scaling delay is relatively short for the
acoustic echo suppression application.
[0114] Given equation (14) and the scaled adaptive gain of equation
(10), the goal then becomes to determine the scaled fixed codebook
gain, such that E x ( s ) = G 2 .times. n = 0 N - 1 .times. w 2
.function. ( n ) = n = 0 N - 1 .times. ( w ' .function. ( n ) ) 2 (
16 ) ##EQU10##
[0115] where w'(n) is the total excitation corresponding to the
scaled bit stream, so, 140b and is given by w ' .function. ( n ) =
g p ' .times. v ' .function. ( n ) + g c ' .times. c .function. ( n
) ( 16 ) ##EQU11##
[0116] Note that the fixed codebook vector, c(n), is the same as
the fixed codebook vector in equation (12) for w(n) since the
scaling does not modify the fixed codebook vector. The goal then
becomes: G 2 .times. n = 0 N - 1 .times. w 2 .function. ( n ) = n =
0 N - 1 .times. ( g p ' .times. v ' .function. ( n ) + g c '
.times. c .function. ( n ) ) 2 ( 17 ) ##EQU12##
[0117] The adaptive codebook gain, g'.sub.p, is determined by
equations (10) and (11). However, to preserve the speech energy at
the decoder, the quantized version of the gain, '.sub.p, is used in
Equation (17), resulting in G 2 .times. n = 0 N - 1 .times. w 2
.function. ( n ) = n = 0 N - 1 .times. ( g ^ p ' .times. v '
.function. ( n ) + g c ' .times. c .function. ( n ) ) 2 ( 18 )
##EQU13##
[0118] Equation (18) can be rewritten as a quadratic equation in
g'.sub.c as: ( n = 0 N - 1 .times. c 2 .function. ( n ) ) .times. (
g c ' ) 2 + ( 2 .times. n = 0 N - 1 .times. g ^ p ' .times. v '
.function. ( n ) .times. c .function. ( n ) ) .times. g c ' + ( n =
0 N - 1 .times. ( g ^ p ' .times. v ' .function. ( n ) ) 2 - G 2
.times. n = 0 N - 1 .times. w 2 .function. ( n ) ) = 0 ( 19 )
##EQU14##
[0119] Solving for the roots of the quadratic equation (19), the
scaled fixed codebook gain, g'.sub.c, is set to the positive
real-valued root. In the event that both roots are real and
positive, either root can be chosen. One strategy that may be used
is to set g'.sub.c to the root with the larger value. Another
strategy is to set g'.sub.c to the root that gives the closer value
to Gg.sub.c. The scale factor for the fixed codebook gain is then
given by, K c = g c ' g c ( 20 ) ##EQU15##
[0120] where g'.sub.c is a positive real-valued root of equation
(19).
[0121] In some rare cases, no positive real-valued root exists for
equation (19). The roots are either negative real-valued or
complex, implying no valid answer exists for g'.sub.c. This can be
due to the effects of quantization. In these cases, a back-off
scaling procedure may be performed, where K.sub.c is set to zero,
and the scaled adaptive codebook gain is determined by preserving
the energy of the total excitation. That is, K p = G .function. [ n
= 0 N - 1 .times. w 2 .function. ( n ) n = 0 N - 1 .times. ( v '
.function. ( n ) ) 2 ] 1 / 2 ( 21 ) ##EQU16##
[0122] Experimental Results
[0123] To examine the performance of the JCS method, it may be
compared it to the method where g.sub.c is scaled by the desired
scaling factor, G, similar to what is proposed in Beaugeant et al.,
supra. For reference, this method is referred to herein as the
"Fixed Codebook Scaling" method.
[0124] FIG. 8 shows a 12.2 kbps AMR decoded speech signal
representing a sentence spoken by a female speaker. FIG. 9 shows
the energy contour of this signal, where the energy is computed on
5 msec. segments. Superimposed on the energy contour in FIG. 9 is
an example of a desired scale factor contour by which it is
preferable to scale the signal in its coded domain, for reasons
described above. This scale factor contour is manually constructed
so as to have varying scaling conditions and scaling
transitions.
[0125] The JCS method described above was applied to in this
example. After performing the parameter scaling, the resulting bit
stream was decoded into a linear domain signal. As the decoding
operation was performed, the synthesized LPC excitation signal was
also saved. The ratio of the energy of the LPC excitation signal
corresponding to the scaled parameter bit stream to the energy of
the LPC excitation corresponding to the original non-scaled
parameter bit stream was then computed. Specifically, the following
equation was computed R e = n = 0 N - 1 .times. ( w ' .function. (
n ) ) 2 n = 0 N - 1 .times. w 2 .function. ( n ) ( 22 )
##EQU17##
[0126] The excitation signal w'(n) in Equation (22) is the actual
excitation signal seen at the decoder (i.e., after re-quantization
of the scaled gain parameters). Ideally, R.sub.e should track as
much as possible the scale factor contour given in FIG. 9.
[0127] FIG. 10 shows a comparison of the ratio, R.sub.e, between
the JCS method and the Fixed Codebook Scaling method. It is clear
from this figure, the JCS method tracks more closely the desired
scaling factor contour. The ultimate goal, however, is to scale the
resulting decoded speech signal.
[0128] FIG. 11 shows the energy contour of the decoded speech
signal using the JCS method superimposed on the desired energy
contour of the decoded speech signal. This desired contour is
obtained by multiplying (or adding in the log scale) the energy
contour in FIG. 9 by the desired scaling factor that is
superimposed on FIG. 9.
[0129] FIG. 12 is a similar plot for the Fixed Codebook Scaling. It
can also be seen here that the JCS results in a better tracking of
the desired speech energy contour.
[0130] CD-AES with Spectrally Matched Noise Injection (SMNI)
[0131] Typically in echo suppression, it is desirable to heavily
suppress the signal when it is detected that there is only far end
speech with no near end speech and that an echo is present in the
send-in signal. This heavy suppression significantly reduces the
echo, but it also introduces discontinuity in the signal, which can
be discomforting or annoying to the far end listener. To remedy
this, comfort noise is typically injected to replace the suppressed
signal. The comfort noise level is computed based on the signal
power of the background noise at the near end, which is determined
during periods when neither the far end user nor the near end user
is talking. Ideally, to make the signal even more natural sounding,
the spectral characteristics of the comfort noise needs to match
closely a background noise of the near end. When echo suppression
is performed in the linear domain, Spectrally Matched Noise
Injection (SMNI) is typically done by averaging a power spectrum
during segments of no speech activity at both ends and then
injecting this average power spectrum when the signal is to be
suppressed. However, this procedure is not directly applicable to
the coded domain. Here, a method and corresponding apparatus for
SMNI is provided in the coded domain.
[0132] FIG. 13A is a block diagram of another exemplary embodiment
of a CD-AES system 1300 that can be used to implement the CD-AES
system 130b of FIGS. 4 and 7A. The Coded Domain Acoustic Echo
Suppressor 1300 of FIG. 13A includes an SMNI processor 1305. The
idea of the coded domain SMNI is to compute near end background
noise spectral characteristics by averaging an amplitude spectrum
represented by the LPC coefficients during periods when neither
speaker (i.e., near-end and far-end) is speaking. Specifically, the
CD-SMNI processor 1305 computes new {a.sub.i(m)}, c.sub.m(n),
g.sub.c(m), and g.sub.p(m) parameters 1320 when the signal 140a is
to be heavily suppressed.
[0133] The inputs to the CD-SNMI processor 1305 are as follows:
[0134] (i) the decoded LPC coefficients {a.sub.i(m)};
[0135] (ii) the decoded fixed codebook vector C.sub.m(n);
[0136] (iii) The decoded send-out speech signal, so(n);
[0137] (iv) a Voice Activity Detector signal, VAD(n), which is
typically determined as part of the Linear-Domain Echo Suppression.
This signal indicates whether the near end is speaking or not;
and
[0138] (v) a Double Talk Detector signal, DTD(n), which is
typically determined as part of the Linear-Domain Echo Suppression
305a. This signal indicates whether both near-end and far-end
speakers 105a, 105b are talking at the same time.
[0139] During frames when both VAD(n) and DTD(n) 1315 indicate no
activity, implying no speech on either end of the call, the CD-SMNI
processor 1305 computes a running average of the spectral
characteristics of the signal 140a. The technique used to compute
the spectral characteristics may be similar to the method used in a
standard AMR codec to compute the background noise characteristics
for use in its silence suppression feature. Basically, in the AMR
codec, the LPC coefficients, in the form of line spectral
frequencies, are averaged using a leaky integrator with a time
constant of eight frames. The decoded speech energy is also
averaged over the last eight frames. In the CD-SMNI processor 1305,
a running average of the line spectral frequencies and the decoded
speech energy is kept over the last eight frames of no speech
activity on either end. When the CD-AES heavily suppresses the
signal 140a (e.g., by more than 10 dB), the SMNI processor 1305 is
activated to modify the send-in bit stream 140a and send, by way of
a switch 1310 (which may be mechanical, electrical, or software),
new coder parameters 1320 so that, when decoded at the far end,
spectrally matched noise is injected. This noise injection is
similar to the noise injection done during a silence insertion
feature of the standard AMR decoder.
[0140] When noise is to be injected, the CD-SMNI processor 1305
determines new LPC coefficients, {a'.sub.i(m)}, based on the above
mentioned averaging. Also, a new fixed codebook vector,
c'.sub.m(n), and a new fixed codebook gain, g'.sub.c(m), are
computed. The fixed codebook vector is determined using a random
sequence, and the fixed codebook gain is determined based on the
above mentioned decoded speech energy. The adaptive codebook gain,
g'.sub.p(m), is set to zero. These new parameters 1320 are
quantized 325 and inserted 335 into the send-in bit stream 140a to
produce the send-out bit stream 140b.
[0141] Note that, in contrast to FIG. 7A, the decoder 340b
operating on the send-out bit stream, so, 140b in FIG. 13A is no
longer a partial decoder since SMNI needs to have access to the
decoded speech signal. However, since the decoded speech is used to
compute its energy, the AMR decoder 340b can be partial in the
sense that post-filtering need not be performed.
[0142] FIG. 13B is a flow diagram corresponding to the CD-AES
system of FIG. 13A. In the flow diagram, example internal
activities occurring in the SMNI processor 1305 are illustrated,
which include a determination 1325 as to whether voice activity is
detected and a determination 1330 whether double talk is present
(i.e., whether both users 105a, 105b are speaking concurrently). If
both determinations 1325, 1330 are false (i.e., there is silence on
the line), then a spectral estimate for noise injection 1335 is
updated. Thereafter, a determination 1340 as to whether the LD-AES
heavily suppresses the signal is made. If it does, then the noise
injection spectral estimate parameters are quantized 1345, and the
switch 1310 is activated by a switch control signal 1350 to pass
the quantized noise injection parameters. If the LD-AES does not
heavily suppress the signal, then the switch 1310 allows the
quantized, adaptive and fixed codebook gains that are determined by
the JCS process to pass.
[0143] Coded Domain Noise Reduction (CD-NR)
[0144] A method and corresponding apparatus for performing noise
reduction directly in the coded domain using an exemplary
embodiment of the present invention is now described. As should
become clear, no intermediate decoding/re-encoding is performed,
thereby avoiding speech degradation due to tandem encodings and
also avoiding significant additional delays.
[0145] FIG. 14 is a block diagram of the network 100 employing a
Coded Domain Noise Reduction (CD-NR) system 130c, where noise
reduction is shown on both sides of the call. One side of the call
is referred to herein as the near end 135a, and the other side of
the call is referred to herein as the far end 135b. In this figure,
the receive-in signal, ri, 145a, the send-in signal, si, 140a, and
the send-out signal, so, 140b are bit streams representing
compressed speech. Since the two noise reduction systems 130c are
identical in operation, the description below focuses on the noise
reduction system 130c that operates on the send-in signal, si,
140a.
[0146] The CD-NR system 130c presented herein is applicable to the
family of speech coders based on Code Excited Linear Prediction
(CELP). According to an exemplary embodiment of the present
invention, the AMR set of coders is considered an example of CELP
coders. However, the method for CD-NR presented herein is directly
applicable to all coders based on CELP. Moreover, although the VQE
processors described herein are presented in reference to
CELP-based systems, the VQE processors are more generally
applicable to any form of communications system or network that
codes and decodes communications or data signals in which VQE
processors or other processors can operate in the coded domain.
[0147] Three different methods of Coded Domain Noise Reduction are
presented immediately below.
[0148] Method 1
[0149] A Coded Domain Noise Reduction method and corresponding
apparatus is described herein whose performance approximates the
performance of a Linear Domain-Noise Reduction technique. To
accomplish this performance, after performing Linear-Domain Noise
Reduction (LD-NR), the CD-NR system 130c extracts relevant
information from the LD-NR processor. This information is then
passed to a coded domain noise reduction processor.
[0150] FIG. 15 is a high level block diagram of the approach taken.
An exemplary CD-NR system 1500 may be used to implement the CD-NR
system 130c introduced in FIG. 14. In FIG. 15, only the near-end
side 135a of the call is shown, where noise reduction is performed
on the send-in bit stream, si, 140a. The send-in bit stream 140a is
decoded into the linear domain, si(n), 210a and then passed through
a conventional LD-NR system 305b to reduce the noise in the si(n)
signal 210a. Relevant information 215, 225 is extracted from both
LD-NR and the AMR decoding processors 305b, 205a, and then passed
to the coded domain processor 1500. The coded domain processor 1500
modifies the appropriate parameters in the si bit stream 140a to
effectively reduce noise in the signal.
[0151] It should be understood that the AMR decoding 205a can be a
partial decoding of the send-in signal 140a. For example, since
LD-NR is typically concerned with noise estimation and reduction,
the post-filter present in the AMR decoder 205a need not be
implemented. It should further be understood that, although the si
signal 140a is decoded 205a into the linear domain, no intermediate
decoding/re-encoding, which can degrade the speech quality, is
being introduced. Rather, the decoded signal 210a is used to
extract relevant information 225 that aids the coded domain
processor 1500 and is not re-encoded after the LD-NR processor 305b
is performed.
[0152] FIG. 16A shows a detailed block diagram of another exemplary
embodiment of a CD-NR system 1600 used to implement the CD-NR
systems 130c and 1500. Typically, the LD-NR system 305b decomposes
the signal into its frequency-domain components using a Fast
Fourier Transform (FFT). In most implementations, the frequency
components range between 32 and 256. Noise is estimated in each
frequency component during periods of no speech activity. This
noise estimate in a given frequency component is used to reduce the
noise in the corresponding frequency component of the noisy signal.
After all the frequency components have been noise reduced, the
signal is converted back to the time-domain via an inverse FFT.
[0153] An important observation about the Linear Domain Noise
Reduction is that if a comparison of the energy of the original
signal si(n) 210a to the energy of the noise reduced signal
si.sub.r(n) is made, one finds that different speech segments are
scaled differently. For example, segments with high Signal-to-Noise
Ratio (SNR) are scaled less than segments with low SNR. The reason
for that lies in the fact that noise reduction is being done in the
frequency domain. It should be understood that the effect of LD-NR
in the frequency domain is more complex than just segment-specific
time-domain scaling. But, one of the most audible effects is the
fact that the energy of different speech segments are scaled
according to their SNR. This gives motivation to the CD-NR using an
exemplary embodiment of the present invention, which transforms the
problem of Noise Reduction in the coded domain to one of adaptively
scaling the signal.
[0154] The scaling factor 315 for a given frame is the ratio
between the energy of the noise reduced signal, si.sub.r(n), and
the original signal, si(n) 210a. The "Coded Domain Parameter
Modification" unit 320 in FIG. 16A is the Joint Codebook Scaling
(JCS) method described above. In JCS, both the CELP adaptive
codebook gain, g.sub.p(m), and the fixed codebook gain,
g'.sub.c(m), are scaled. They are then quantized 325 and inserted
335 in the send-out bit stream, so, 140b replacing the original
gain parameters present in the si bit stream 140a. These scaled
gain parameters, when used along with the other decoder parameters
215 in the AMR decoding processor 205a, produce a signal that is an
adaptively scaled version of the original noisy signal, si(n),
210a, which produces a reduced noise signal approximating the
reduced noise, linear domain signal, si.sub.r(n), which may be
referred to as a target signal.
[0155] Below is a summary of the operations in the proposed CD-NR
system 1600 shown in FIG. 16A and presented in the form of a flow
diagram in FIG. 16B:
[0156] (i) The bit stream si 140a is decoded into a linear domain
signal, si(n) 210a.
[0157] (ii) A Linear-Domain Noise Reduction system 305b that
operates on si(n) 210a is performed. The LD-NR output is the signal
si.sub.r(n), which represents the send-in signal, si(n), 210a after
noise is reduced and may be referred to as the target signal.
[0158] (iii) A scale computation 310 that determines the scaling
factor 315 between si(n) 210a and si.sub.r(n) is performed. A
single scaling factor, G(m), 315 is computed for every frame (or
subframe) by buffering a frame worth of samples of si(n) 210a and
si.sub.r(n) and determining the ratio between them. Here, the
index, m, is the frame number index. One possible method for
computing G(m) 315 is a simple power ratio between the two signals
in a given frame. Other methods include computing a ratio of the
absolute value of every sample of the two signals in a frame, and
then taking a median or average of the sample ratio for the frame,
and assigning the result to G(m) 315. The scale factor 315 can be
viewed as the factor by which a given frame of si(n) 210a has to be
scaled to reduce the noise in the signal. The frame duration of the
scale computation is equal to the subframe duration of the CELP
coder. For example, in the AMR 12.2 kbps coder 205a, the subframe
duration is 5 msec. The scale computation frame duration is
therefore set to 5 msec.
[0159] (iv) The scaling factor, G(m), 315 is used to determine a
scaling factor for both the adaptive codebook gain and the fixed
codebook gain parameters of the coder. The Coded-Domain Parameter
Modification unit 320 employs the Joint Codebook Scaling method to
scale g.sub.p(m) and g.sub.c(m).
[0160] (v) The scaled gains are quantized 325 and inserted 335 into
the send-out bit stream, so, 140b by substituting the original
quantized gains in the si bit stream 140a.
[0161] Method 2
[0162] FIG. 17A is a block diagram illustrating another exemplary
embodiment of a CD-NR system 1700 used to implement the CD-NR
systems 130c, 1500. In this embodiment, the linear domain
noise-reduced signal, Si.sub.r(n), is re-encoded by a partial
re-encoder 1705. However, the re-encoding is not a full
re-encoding. Rather, it is partial in the sense that some of
encoded parameters in the send-in signal bit stream, si, 140a are
kept, while others are re-estimated and re-quantized. In one
example implementation, the LPC parameters, {a'(m)}, and the pitch
lag value, T(m), are kept the same as what is contained in the si
bit stream 140a. The adaptive codebook gain, g.sub.p(m), the fixed
codebook vector, c.sub.m(n), and the fixed codebook gain,
g.sub.c(m), are re-estimated, re-quantized, and then inserted into
the send-out bit stream, so, 140b. Re-estimating these parameters
is the same process used in the regular AMR encoder. The difference
is that, in the re-encoding processor 1705, the LPC parameters,
{a'(m)}, and the pitch lag value, T(m), are not re-estimated but
assigned the specific values corresponding to the si bit stream
140a. As such, this re-encoding 1705 is a partial re-encoding.
[0163] FIG. 17B is a flow diagram of a method corresponding to the
embodiment of the CD-NR system 1700 of FIG. 7A.
[0164] Method 3
[0165] Comparing Method 1 to Method 2 for CD-NR, it is noted that
one of the major differences between them is that the fixed
codebook vector, c.sub.m(n), is re-estimated in Method 2. This
re-estimation is performed using a similar procedure to how
c.sub.m(n) is -estimated in the standard AMR encoder. It is well
known, however, that the computational requirements needed for
re-estimating c.sub.m(n) is rather large. It is also useful to note
that at relatively medium to high Signal-to-Noise Ratio (SNR), the
performance of Method 1 matches very closely the performance of the
Linear Domain Noise Reduction system. At relatively low SNR, there
is more audible noise in the speech segments of Method 1 compared
to the LD-NR system 305b. Method 2 can reduce this noise in the low
SNR cases. One way to incorporate the advantages of Method 2,
without the full computational requirements needed for Method 2, is
to combine Method 1 and 2 in the following way. A byproduct of most
Linear-Domain Noise Reduction is an on-going estimate of the
Signal-to-Noise Ratio of the original noisy signal. This SNR
estimate can be generated for every subframe. If it is detected
that the SNR is medium to large, follow the procedure outlined in
Method 1. If it is detected that the SNR is relatively low, follow
the procedure outlined in Method 2.
[0166] Coded Domain Adaptive Level Control (CD-ALC)
[0167] A method and corresponding apparatus for performing adaptive
level control directly in the coded domain using an exemplary
embodiment of the present invention is now presented. As should
become clear, no intermediate decoding/re-encoding is performed,
thus avoiding speech degradation due to tandem encodings and also
avoiding significant additional delays.
[0168] FIG. 18 is a block diagram of the network 100 employing a
Coded Domain Adaptive Level Control (CD-ALC) system 130d using an
exemplary embodiment of the present invention, where the adaptive
level control is shown on both sides of the call. One side of the
call is referred to herein at the near end 135a and the other side
is referred to herein as the far end 135b. In this figure, the
receive-in signal, ri, 145a, the send-in signal, si, 140a, and the
send-out signal, so, 140b are bit streams representing compressed
speech. Since the two adaptive level control systems 130d are
identical in operation, the description below focuses on the CD-ALC
system 130d that operates on the send-in signal, si, 140a.
[0169] The CD-ALC method and corresponding apparatus presented
herein is applicable to the family of speech coders based on Code
Excited Linear Prediction (CELP). According to an exemplary
embodiment of the present invention, the AMR set of coders is
considered as an example of CELP coders. However, the method and
corresponding apparatus for CD-ALC presented herein is directly
applicable to all coders based on CELP.
[0170] A Coded Domain Adaptive Level Control method and
corresponding apparatus are described herein whose performance
matches the performance of a corresponding Linear-Domain Adaptive
Level Control technique. To accomplish this matching performance,
after performing Linear-Domain Adaptive Level Control (LD-ALC), the
CD-ALC system 130d extracts relevant information from the LD-ALC
processor 305c. This information is then passed to the Coded Domain
Adaptive Level Control system 130d.
[0171] FIG. 19 shows a high level block diagram of an exemplary
embodiment of a CD-ALC system 1900 that can be used to implement
the CD-ALC system of FIG. 18. In FIG. 19, only the near-end side
135a of the call is shown, where Adaptive Level Control is
performed on the send-in bit stream, si, 140a. The send-in bit
stream 140a is decoded into the linear domain, si(n), 210a and then
passed through a conventional LD-ALC system 305c to adjust the
level of the si(n) signal 210a. Relevant information 225, 215 is
extracted from both LD-ALC and the AMR decoding processors 305c,
205a, and then passed to the coded domain processor 230d. The coded
domain processor 230d modifies the appropriate parameters in the si
bit stream 140a to effectively reduce noise in the signal.
[0172] It should be understood that the AMR decoding 205a can be a
partial decoding of the send-in bit stream signal 140a. For
example, since LD-ALC processor 305c is typically concerned with
determining signal levels, the post-filter present in the AMR
decoder 205a need not be implemented. It should further be
understood that, although the si signal 140a is decoded into the
linear domain, no intermediate decoding/re-encoding, which can
degrade the speech quality, is being introduced. Rather, the
decoded signal 210a is used to extract relevant information 215,
225 that aids the coded domain processor 230d and is not re-encoded
after the LD-ALC processor 1900.
[0173] FIG. 20A is a detailed block diagram of an exemplary
embodiment of a CD-ALC system 2000 that can be used to implement
the CD-ALC systems 130d, 1900. The CD-ALC system 2000 also includes
an embodiment of a coded domain processor 2002 introduced as the
coded domain processor 230d in FIGS. 2 and 19. Typically, the
LD-ALC system 305c determines an adaptive scaling factor 315 for
the signal on a frame by frame basis, so the problem of Adaptive
Level Control in the coded domain is transformed to one of
adaptively scaling the signal 140a. The scaling factor 315 for a
given frame is determined by the LD-ALC processor 305c. The "Coded
Domain Parameter Modification" unit 320 in FIG. 20A may be the
Joint Codebook Scaling (JCS) method described above. In JCS, both
the CELP adaptive codebook gain and the fixed codebook gain are
scaled. They are then quantized 325 and inserted 335 in the
send-out bit stream, so, 140b, replacing the original gain
parameters present in the si bit stream 140a. These scaled gain
parameters, when used along with the other decoder parameters 215
in the AMR decoding processor 205a, produce a signal that is an
adaptively scaled version of the original signal, si(n), 210a.
[0174] The operations in the CD-ALC system 2000 shown in FIG. 20A
are summarized immediately below and presented in flow diagram form
in FIG. 20B:
[0175] (i) The bit stream si is decoded into the linear signal,
si(n).
[0176] (ii) A Linear-Domain Adaptive Level Control system 305c that
operates on si(n) is performed. The LD-ALC output is the signal
si.sub.v(n) which represents the send-in signal, si(n), 210a after
adaptive level control and may be referred to as the target
signal.
[0177] (iii) A scale computation 310 that determines the scaling
factor 315 between si(n) 210a and si.sub.v(n) is performed. A
single scaling factor, G(m), 315 is computed for every frame (or
subframe) by buffering a frame worth of samples of si(n) 210a and
si.sub.v(n) and determining the ratio between them. Here, the
index, m, is the frame number index. One possible method for
computing G(m) 315 is a simple power ratio between the two signals
in a given frame. Other methods include computing a ratio of the
absolute value of every sample of the two signals in a frame, and
then taking a median or average of the sample ratio for the frame,
and assigning the result to G(m) 315. The scale factor 315 can be
viewed as the factor by which a given frame of si(n) 210a has to be
scaled to reduce the noise in the signal. The frame duration of the
scale computation is equal to the subframe duration of the CELP
coder. For example, in the AMR 12.2 kbps coder 205a, the subframe
duration is 5 msec. The scale computation frame duration is
therefore set to 5 msec.
[0178] (iv) The scaling factor, G(m), 315 is used to determine a
scaling factor for both the adaptive codebook gain and the fixed
codebook gain parameters of the coder. The Coded-Domain Parameter
Modification unit 320 employs the Joint Codebook Scaling method to
scale g.sub.p(m) and g.sub.c(m).
[0179] (v) The scaled gains are quantized and inserted into the
send-out bit stream, so, 140b by substituting the original
quantized gains in the si bit stream 140a.
[0180] Coded Domain Adaptive Gain Control (CD-AGC)
[0181] A method and corresponding apparatus for performing adaptive
gain control directly in the coded domain using an exemplary
embodiment of the present invention is now presented. As should
become clear, no intermediate decoding/re-encoding is performed,
thus avoiding speech degradation due to tandem encodings and also
avoiding significant additional delays.
[0182] FIG. 21 is a block diagram of the network 100 employing a
Coded Domain Adaptive Gain Control (CD-AGC) system 130e, where the
adaptive gain control is shown in one direction. One call side is
referred to herein as the near end 135a, and the other call side is
referred to herein as the far end 135b. In this figure, the
receive-in signal, ri, 145a, the send-in signal, si, 140a, and the
send out signal, so, 140b are bit streams representing compressed
speech. Since the adaptive gain control systems 130e for both
directions are identical in operation, focus herein is on the
system 130e that operates on the send-in signal, si, 140a.
[0183] The CD-AGC method and corresponding apparatus presented
herein is applicable to the family of speech coders based on Code
Excited Linear Prediction (CELP). According to an exemplary
embodiment of the present invention, the AMR set of coders is
considered as an example of CELP coders. However, the method and
corresponding apparatus for CD-AGC presented herein is directly
applicable to all coders based on CELP.
[0184] FIG. 22 is a high level block diagram of an exemplary
embodiment of an LD-AGC system 2200 used to implement the LD-AGC
system 130e introduced in FIG. 21. Referring to FIG. 22, the basic
approach of the method and corresponding apparatus for Coded Domain
Adaptive Gain Control according to the principles of the present
invention makes use of advances that have been made in the
Linear-Domain Adaptive Gain Control Field. A Coded Domain Adaptive
Gain Control method and corresponding apparatus are described
herein whose performance matches the performance of a corresponding
Linear-Domain Adaptive Gain Control (LD-AGC) technique. To
accomplish this matching performance, the LD-AGC is used to
calculate the desired gain for adaptive gain control. This
information is then passed to the Coded Domain Adaptive Gain
Control.
[0185] Specifically, FIG. 22 is a high level block diagram of the
approach taken. In this figure, Adaptive Gain Control is performed
on the send-in bit stream, si. The send-in and receive-in bit
streams 140a, 145a are decoded 205a, 205b into the linear domain,
si(n) 210a and ri(n) 210b, and then passed through a conventional
LD-AGC system 305d to adjust the level of the si(n) signal 210a.
Relevant information 225, 215 is extracted from both LD-AGC and the
AMR decoding processors 305d, 205a, and then passed to the coded
domain processor 230e. The coded domain processor 230e modifies the
appropriate parameters in the si bit stream 140a to effectively
adjust its level.
[0186] It should be understood that the AMR decoding 205a, 205b can
be a partial decoding of the two signals 140a, 145a. For example,
since LD-AGC is typically concerned with determining signal levels,
the post-filter (H.sub.m(z), FIG. 5) present in the AMR decoder
205a, 205b need not be implemented. It should further be understood
that, although the si signal 140a is decoded into the linear
domain, no intermediate decoding/re-encoding that can degrade the
speech quality is being introduced. Rather, the decoded signal 210a
is used to extract relevant information that aids the coded domain
processor 230e and is not re-encoded after the LD-AGC processor
305d.
[0187] FIG. 23A is a detailed block diagram of an exemplary
embodiment of a CD-AGC system 2300 used to implement the CD-AGC
systems 130e and 2200. Typically, the LD-AGC system 2200 determines
an adaptive scaling factor 315 for the signal on a frame by frame
basis. Therefore, the problem of Adaptive Gain Control in the coded
domain can be considered one of adaptively scaling the signal. The
scaling factor 315 for a given frame is determined by the LD-AGC
processor 305d. The CD-AGC system 2300 includes an exemplary
embodiment of a coded domain processor 2302 used to implement the
coded domain processor 230e of FIG. 22. A "Coded Domain Parameter
Modification" unit 320 in FIG. 23A may employ the Joint Codebook
Scaling (JCS) method described above. In JCS, both the CELP
adaptive codebook gain, g.sub.p(m), and the fixed codebook gain,
g.sub.c(m), are scaled. They are then quantized 325 and inserted
335 in the send-out bit stream, so, 140b replacing the original
gain parameters present in the si bit stream 140a. These scaled
gain parameters, when used along with the other decoder parameters
215 in the AMR decoding processor 205a, produce a signal that is an
adaptively scaled version of the original signal, si(n), 210a.
[0188] The operations in the CD-AGC system 2300 shown in FIG. 23A
and presented in flow diagram form in FIG. 23B are summarized
immediately below:
[0189] (i) The receive input signal bit stream ri 145a is decoded
into the linear domain signal, ri(n), 210b.
[0190] (ii) The send-in bit stream si 140a is decoded into the
linear domain signal, si(n), 210a.
[0191] (iii) A Linear-Domain Adaptive Gain Control system 305d that
operates on ri(n) 210b and si(n) 210a is performed. The LD-AGC
output is the signal, si.sub.g(n) which represents the send-in
signal, si(n), 210a after adaptive gain control and may be referred
to as the target signal.
[0192] (iv) A scale computation 310 that determines the scaling
factor 315 between si(n) 210a and si.sub.g(n) is performed. A
single scaling factor, G(m), 315 is computed for every frame (or
subframe) by buffering a frame worth of samples of si(n) 210a and
si.sub.v(n) and determining the ratio between them. Here, the
index, m, is the frame number index. One possible method for
computing G(m) 315 is a simple power ratio between the two signals
in a given frame. Other methods include computing a ratio of the
absolute value of every sample of the two signals in a frame, and
then taking a median or average of the sample ratio for the frame,
and assigning the result to G(m) 315. The scale factor 315 can be
viewed as the factor by which a given frame of si(n) 210a has to be
scaled to reduce the noise in the signal. The frame duration of the
scale computation is equal to the subframe duration of the CELP
coder. For example, in the AMR 12.2 kbps coder 205a, the subframe
duration is 5 msec. The scale computation frame duration is
therefore set to 5 msec.
[0193] (v) The scaling factor, G(m), 315 is used to determine a
scaling factor for both the adaptive codebook gain and the fixed
codebook gain parameters of the coder. The Coded-Domain Parameter
Modification unit 320 employs the Joint Codebook Scaling method to
scale g.sub.p(m) and g.sub.c(m)
[0194] (vi) The scaled gains are quantized 325 and inserted 335
into the send-out bit stream, so, 140b by substituting the original
quantized gains in the si bit stream 140a.
[0195] CD-VQE Distributed about a Network
[0196] FIG. 24 is a network diagram of an example network 2400 in
which the CD-VQE system 130a, or subsets thereof, are used in
multiple locations such that calls between any endpoints, such as
cell phones 2405a, IP phones 2405b, traditional wire line
telephones 2405c, personal computers (not shown), and so forth can
involve the CD-VQE process(ors) disclosed herein above. The network
2400 includes Second Generation (2G) network elements and Third
Generation (3G) network elements, as well as Voice-over-IP (VoIP)
network elements.
[0197] For example, in the case of a 2G network, the cell phone
2405a includes an adaptive multi-rate coder and transmits signals
via a wireless interface to a cell tower 2410. The cell tower 2410
is connected to a base station system 2410, which may include a
Base Station Controller (BSC) and Transmitter/Receiver Access Unit
(TRAU). The base station system 2410 may use Time Division
Multiplexing (TDM) signals 2460 to transmit the speech to a media
gateway system 2435, which includes a media gateway 2440 and a
CD-VQE system 130a.
[0198] The media gateway system 2435 in this example network 2400
is in communication with an Asynchronous Transfer Mode (ATM)
network 2425, Public Switched Telephone Network (PSTN) 2445, and
Internet Protocol (IP) network 2430. The media gateway system 2435,
for example, converts the TDM signals 2460 received from a 2G
network into signals appropriate for communicating with network
nodes using the other protocols, such as IP signals 2465,
Iu-cs(AAL2) signals 2470b, Iu-ps(AAL5) signals 2470a, and so forth.
The media gateway system 2435 may also be in communication with a
softswitch 2450, which communicates through a media server 2455
that includes a CD-VQE 130a.
[0199] It should be understood that the network 2400 may include
various generations of networks, and various protocols within each
of the generations, such as 3G-R'4 and 3G-R'5. As described above,
the CD-VQE 130a, or subsets thereof may be deployed or associated
with any of the network nodes that handle coded domain signals.
Although endpoints (e.g., phones) in a 3G or 2G network can perform
VQE, using the CD-VQE system 130a, within the network can improve
VQE performance since endpoints have very limited computational
resources compared with network based VQE systems. Therefore, more
computational intensive VQE algorithms can be implemented on a
network based VQE systems as compared to an endpoint. Also, battery
life of the endpoints, such as the cellular telephone 2405a, can be
enhanced because the amount of processing required by the
processors described herein tends to use a lot of battery power.
Thus, higher performance VQE will be attained by inner network
deployment.
[0200] For example, the CD-VQE system 130a, or subsystems thereof,
may be deployed in a media gateway, integrated with a base station
at a Radio Network Controller (RNC), deployed in a session border
controller, integrated with a router, integrated or alongside a
transcoder, deployed in a wireless local loop (either standalone or
integrated), integrated into a packet voice processor for
Voice-over-Internet Protocol (VoIP) applications, or integrated
into a coded domain transcoder. In VoIP applications, the CD-VQE
may be deployed in an Integrated Multi-media Server (IMS) and
conference bridge applications (e.g., a CD-VQE is supplied to each
leg of a conference bridge) to improve announcements.
[0201] In a Local Area Network (LAN), the CD-VQE may be deployed in
a small scale broadband router, Wireless Maximization (WiMax)
system, Wireless Fidelity (WiFi) home base station, or within or
adjacent to an enterprise gateway. Using exemplary embodiments of
the present invention, the CD-VQE may be used to improve acoustic
echo control or non-acoustic echo control, improve error
concealment, or improve voice quality.
[0202] Although, described in reference to telecommunications
services, it should be understood that the principles of the
present invention extend beyond telecommunications and to other
areas of telecommunications. For example, other exemplary
embodiments of the present invention include wideband Adaptive
Multi-Rate (AMR) applications, music with wideband AMR video
enhancement, or pre-encode music to improve transport, to name a
few.
[0203] Although described herein as being deployed within a
network, other exemplary embodiments of the present invention may
also be employed in handsets, VoIP phones, media terminals (e.g.,
media phone) VQE in mobile phones, or other user interface devices
that have signals being communicated in a coded domain. Other areas
may also benefit from the principles of the present invention, such
as in the case of forcing Tandem Free Operations (TFO) in a 2G
network after 3G-to-2G handoff has taken place or in a pure TFO in
a 2G network or in a pure 3G network.
[0204] Other coded domain VQE applications include (1) improved
voice quality inside a Real-time Session Manager (RSM) prior to
handoff to Applications Servers (AS)/Media Gateways (MGW); (2)
voice quality measurements inside a RSM to enforce Service Level
Agreements (SLA's) between different VoIP carriers; (3) many of the
VQE applications listed above can be embedded into the RSM for
better voice quality enforcement across all carrier handoffs and
voice application servers. The CD-VQE may also include applications
associated with a multi-protocol session controller (MSC) which can
be used to enforce Quality of Service (QoS) policies across a
network edge.
[0205] It should be understood that the CD-VQE processors or
related processors described herein may be implemented in hardware,
firmware, software, or combinations thereof. In the case of
software, machine-executable instructions may be stored locally on
magnetic or optical media (e.g., CD-ROM), in Random Access Memory
(RAM), Read-Only Memory (ROM), or other machine readable media. The
machine executable instructions may also be stored remotely and
downloaded via any suitable network communications paths. The
machine-executable instructions are loaded and executed by a
processor or multiple processors and applied as described
hereinabove.
[0206] While this invention has been particularly shown and
described with references to preferred embodiments thereof, it will
be understood by those skilled in the art that various changes in
form and details may be made therein without departing from the
scope of the invention encompassed by the appended claims.
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